Regression Models for Bounded Responses

Functions to fit regression models for bounded responses (e.g., proportions and rates) and binomial data. Available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018) ), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020) ), the beta (Ferrari, S.L.P., and Cribari-Neto, F. (2004) ), the flexible beta-binomial (Ascari, R. and Migliorati, S. (2021) ), the beta-binomial, and the binomial one. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman, A.; Carlin, J. B.; Stern, H. S. and Rubin, D. B. (2014) ). Besides, functions to compute residuals, posterior predictives, goodness-of-fit measures, convergence diagnostics, and graphical representations are provided.


Reference manual

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1.1 by Roberto Ascari, 6 days ago

Browse source code at

Authors: Agnese M. Di Brisco [aut, cre] , Roberto Ascari [aut, cre] , Sonia Migliorati [aut] , Andrea Ongaro [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports methods, Rcpp, rstan, rstantools, loo, bayesplot, ggplot2, Formula, utils, grDevices, faraway

Suggests testthat

Linking to BH, Rcpp, RcppEigen, rstan, StanHeaders

System requirements: GNU make

See at CRAN